DBMS > GeoMesa vs. openGauss vs. OpenQM vs. TerarkDB

System Properties Comparison GeoMesa vs. openGauss vs. OpenQM vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

QpenQM is a high-performance, self-tuning, multi-value DBMS

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Secondary database models

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	1.08
Rank	#183	Overall
	#84	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.geomesa.org

gitee.com/opengauss
opengauss.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

github.com/bytedance/terarkdb

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

docs.opengauss.org/en
gitee.com/opengauss/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

CCRi and others

Huawei and openGauss community

Rocket Software, originally Martin Phillips

ByteDance, originally Terark

Initial release

2014

2019

1993

2016

Current release

4.0.5, February 2024

3.0, March 2022

3.4-12

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

GPLv2, extended commercial license available

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

C, C++, Java

C++

Server operating systems

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

with some exceptions

schema-free

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL 2011

APIs and other access methods

JDBC
ODBC

C++ API
Java API

Supported programming languages

C
C++
Java

.Net
Basic
C
Java
Objective C
PHP
Python

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

horizontal partitioning (by range, list and hash)

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users, groups and roles according to SQL-standard

Access rights can be defined down to the item level

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Recent citations in the news

openGauss Open Source Community Officially Launch
1 July 2020, Huawei

The openGauss powers database industry forward through innovation
6 January 2022, Global Times

About HUAWEI Open Source
9 February 2022, Huawei

provided by Google News

A Chinese company is making the cloud 200x faster · TechNode
3 July 2017, TechNode

provided by Google News

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